Diffusion Trajectories Research Articles

Exploring the knowledge development trajectories of the supply chain finance domain: a main path analysis

PurposeSupply chain finance (SCF), which is able to manage financial flows along the supply chains effectively, has received wide attention from all over the world. Faced with the increasing number of outputs, the purpose of this paper is to investigate the SCF development over the past decades effectively, including the hot topics, knowledge diffusion trajectories and structure.Design/methodology/approachThis paper adopts the keyword co-occurrence cluster and main path analysis (MPA) including four types of main paths, studying the historical development of SCF based on 2,233 papers retrieved from Web of Science during 1970–2019.FindingsThe results show that: (1) the research focuses on several aspects, including trade credit, supply chain management, procurement, health financing and sustainability, etc. and (2) trade credit financing has been the mainstream and the research focus has shifted from one-level trade credit to two-level trade credit. Recently, there is a trend to use game-theoretic models to find the best solutions for members in the supply chain.Originality/valueThis paper addresses the need to investigate the knowledge evolution in the SCF domain. It provides a framework to study the knowledge diffusion trajectories and structure, which helps scholars to handle thousands of papers effectively and deepen their understanding of the history, present and future trends of SCF development.

Vertical Diffusion of Ions within Single Particles during Electrochemical Charging.

Determining the trajectory of ionic transport and diffusion within single electroactive nanomaterials is critical for understanding the charging kinetics and capacity fading associated with ion batteries, with implications for rational design of excellent-performance electrode materials. While the horizontal pathway of mass transport has been feasibly investigated by optical superlocalization methods and electron microscopes, determination on the vertical trajectory has proven a more challenging task. Herein, we developed dual-angle total internal reflection microscopy by simultaneously introducing different angle-dependent illumination depths to trace the optical centroid shifts of nano-objects in the vertical dimension. We first demonstrated the proof of concept by resolving the vertical moving trails of a nanosphere doing Brownian motion and subsequently explored the picture of mass transport in the interior of single Prussian blue (PB) particles during electrochemical cycling. The results indicated that the vertical centroids of single PB particles remained unchanged when ions were inserted or extracted, suggesting an outside-in ionic transport pathway instead of bottom-up trajectory that one would intuitively expect.

The Lipids that Get the Invite to a Caveolar Neck Party

Caveolae are plasma membrane (PM) invaginations that appear as bulbs protruding into the cytoplasm. individual bulbs are connected to the bulk membrane by a highly curved neck with an internal pore. Like other highly curved biological structures (e.g., pores created by membrane compartment fusion and clathrin coated endocytic sites before the vesicle pinches off), caveolar necks are created by cellular protein machinery, and the work done by proteins to create and sustain the high curvature depends on the lipid membrane material properties and distributions. Understanding and quantifying lipid equilibrium distributions requires atomistic detail to resolve specific interactions, but also long timescales to allow sufficient lipid diffusion. To meet both of these demands, we used the special-use Anton supercomputer to attain continuous, long timescale trajectories of lipid diffusion on two pores with different internal radii and a planar bilayer as a control. We used a PM mimetic that balances the necessary lipidic complexity with the necessary simplicity to quantify important lipid-lipid interaction motifs and redistributions on a timescale accessible to all-atom simulations. The multi-microsecond simulations allowed us to test two core hypotheses: i) that ganglioside GM3 and palmitoyl sphingomyelin redistribute to areas of positive curvature, and ii) that cholesterol will preferentially flip-flop into the outer leaflet. Because of the diverse curvature accessible on a caveolar pore, the simulations also allow insight into whether lipids redistribute with respect to both net curvature and Gaussian curvature. Preliminary results indicate that cholesterol is depleted in the narrower neck pore and that phosphatidylcholine lipids are enriched in pore neck pores.

Impact of the central frequency of environment on non-Markovian dynamics in piezoelectric optomechanical devices

The piezoelectric optomechanical devices supply a promising experimental platform to realize the coherent and effective control and measurement of optical circuits working in Terahertz (THz) frequencies via superconducting electron devices typically working in Radio (MHz) frequencies. However, quantum fluctuations are unavoidable when the size of mechanical oscillators enter into the nanoscale. The consequences of the noisy environment are still challenging due to the lack of analytical tools. In this paper, a semi-classical and full-quantum model of piezoelectric optomechanical systems coupled to a noisy bosonic quantum environment are introduced and solved in terms of quantum-state diffusion (QSD) trajectories in the non-Markovian regime. We show that the noisy environment, particularly the central frequency of the environment, can enhance the entanglement generation between optical cavities and LC circuits in some parameter regimes. Moreover, we observe the critical points in the coefficient functions, which can lead the different behaviors in the system. Besides, we also witness the entanglement transfers between macroscopic objects due to the memory effect of the environment. Our work can be applied in the fields of electric/ optical switches, and long-distance distribution in a large-scale quantum network.

Strontium isotope evidence for a trade network between southeastern Arabia and India during Antiquity

Cotton (Gossypium sp.), a plant of tropical and sub-tropical origin, appeared at several sites on the Arabian Peninsula at the end of the 1st mill. BCE-beginning of the 1st mill. CE. Its spread into this non-native, arid environment is emblematic of the trade dynamics that took place at this pivotal point in human history. Due to its geographical location, the Arabian Peninsula is connected to both the Indian and African trading spheres, making it complex to reconstruct the trans-continental trajectories of plant diffusion into and across Arabia in Antiquity. Key questions remain pertaining to: (1) provenance, i.e. are plant remains of local or imported origin and (2) the precise timing of cotton arrival and spread. The ancient site of Mleiha, located in modern-day United Arab Emirates, is a rare and significant case where rich archaeobotanical remains dating to the Late Pre-Islamic period (2nd–3rd c. CE), including cotton seeds and fabrics, have been preserved in a burned-down fortified building. To better understand the initial trade and/or production of cotton in this region, strontium isotopes of leached, charred cotton remains are used as a powerful tracer and the results indicate that the earliest cotton finds did not originate from the Oman Peninsula, but were more likely sourced from further afield, with the north-western coast of India being an isotopically compatible provenance. Identifying the presence of such imported cotton textiles and seeds in southeastern Arabia is significant as it is representative of the early diffusion of the crop in the region, later to be grown extensively in local oases.

Dynamic structure and knowledge diffusion trajectory research in green supply chain

Green supply chain (GSC) practice can help enterprises expand the market share, enhance competitive advantage, achieve the sustainable development and maintain the balance among economic, social and environmental benefits. Based on these advantages, the amount of literatures in this field is gradually expanding especially in recent years. This paper combines the bibliometric and main path analysis (MPA) method to introduce the current status and development trend, and explore the dynamic evolution of knowledge and main research topics of this domain. The main results are as follows: (1) Sarkis J is the most prolific author and Hong Kong Polytechnic University is the most productive institution of this field. (2) Articles on main path mainly focus on the application of GSC in various industries and can be divided into two categories based on the research content, including the evaluation and selection of green practices and green supplier, as well as the identification and evaluation of obstacles and drivers in green supply chain management (GSCM) practices. Moreover, the topics of theoretical innovation of evaluation method, evaluation of entire supply chain performance and circular economy (CE) based on the triple bottom line maybe the possible research direction for scholars. In general, this article not only provides a comprehensive and systematic longitudinal bibliometric overview but also presents the trajectory of knowledge diffusion of GSC domain.

Diffusion SLAM: Localizing Diffusion Sources From Samples Taken by Location-Unaware Mobile Sensors

We consider diffusion fields induced by multiple localised and instantaneous sources. We assume a mobile sensor samples the field, uniformly along a piecewise linear trajectory, which is unknown. The problem we address is the estimation of the amplitudes and locations of the diffusion sources, as well as of the trajectory of the sensor. We first propose a method for diffusion source localisation and trajectory mapping (D-SLAM) in 2D, where we assume the activation times of the sources are known and the evolution of the diffusion field over time is negligible. The reconstruction method we propose maps the measurements obtained using the mobile sensor to a sequence of generalised field samples. From these generalised samples, we can then retrieve the locations of the sources as well as the trajectory of the sensor (up to a 2D orthogonal geometric transformation). We then relax these assumptions and show that we can perform D-SLAM also in the case of unknown activation times, from samples of a time-varying field, as well as in 3D spaces. Finally, simulation results on both synthetic and real data further validate the proposed framework.

Impact of Feature Choice on Machine Learning Classification of Fractional Anomalous Diffusion.

The growing interest in machine learning methods has raised the need for a careful study of their application to the experimental single-particle tracking data. In this paper, we present the differences in the classification of the fractional anomalous diffusion trajectories that arise from the selection of the features used in random forest and gradient boosting algorithms. Comparing two recently used sets of human-engineered attributes with a new one, which was tailor-made for the problem, we show the importance of a thoughtful choice of the features and parameters. We also analyse the influence of alterations of synthetic training data set on the classification results. The trained classifiers are tested on real trajectories of G proteins and their receptors on a plasma membrane.

Identifying the princes base on Altmetrics: An awakening mechanism of sleeping beauties from the perspective of social media.

In science, sleeping beauties (SBs) denotes a special phenomenon of the diffusion of scientific knowledge based on citation trajectories, the awakening of which is also measured through changes in the citations index. However, the rapid advancement of social media has altered the mode of scientific communication and knowledge diffusion. This study aims to re-identify SBs and its Prince from the perspective of comprehensive indicators, which involves the analysis of Altmetrics indexes and Citation index, and investigate the awakening mechanism of A-SB to supplement the research on the awakening mechanism of SBs. By combining Ab index, we redefined the Prince, which makes A-SB receive high attention after a long Sleeping period and reflects the most prominent academic or social behavior that awakens and sustains the Awakening of A-SB. Then we conducted empirical research on the retrieved PLOS Biology collection and examined Prince after identifying the A-SB. The analysis and summary of the characteristics of the identified A-SB and Prince revealed the SBs’ awakening mechanism under the comprehensive trajectory based on Altmetrics from the three dimensions of the influence between the indicators, the overall evolution trajectory of A-SB, and literature bibliometric attributes. In the trajectory of Delayed Recognition stage of A-SB, we define the Dogsleep of SBs, which mirrors that the instability of the Sleeping of SBs will generate a specific negative impact on Prince of A-SB and Awakening intensity. Besides, the literature bibliometric attributes cannot reflect the tendency of users to read academic papers, which again proves that the traditional citation index cannot be neglected in the awakening mechanism of A-SB. Overall, this study demonstrates the addition of the Altmetrics indexes as a useful complement, illustrating the inheritance and connection between the SBs based on the comprehensive trajectory and the SBs based on the citation diffusion trajectory.

Evaluation of Amorphous Oxide Coatings for High-Voltage Li-Ion Battery Applications Using a First-Principles Framework

Surface coatings can effectively suppress cathode degradation and enhance electrochemical performance of lithium-ion batteries. To improve our understanding and rational design of amorphous cathode coating materials, here, we present a framework to explore transport mechanisms and thermodynamic stability in such materials. The framework includes series of ab-initio molecular dynamics (AIMD) simulations to obtain amorphous structures and diffusion trajectories, the analysis of the change in coordinating environments during diffusion, the estimation of room temperature diffusivities and the evaluation of the material's suitability in terms of its ability to facilitate Li+ transport while blocking O2- transport. We apply this framework to two commonly used amorphous coating materials: ZnO and Al2O3. We find that (1) Li+ and O2- diffuse much faster in ZnO than in Al2O3. (2) At a state of high charge, neither Al2O3 nor ZnO is expected to retain a significant amount of Li+. (3) Al2O3 provides a better conformal cathode coating than ZnO. We believe this framework can be productively used to evaluate other amorphous materials for different performance metrics and facilitate the development of optimal cathode coatings.

Innovation adoption: Broadcasting versus virality

AbstractDiffusion channels are critical to determining the adoption scale, which leads to the ultimate impact of an innovation. The aim of this study is to develop an integrative understanding of the impact of two diffusion channels (i.e., broadcasting vs. virality) on innovation adoption. Using citations of a series of classic algorithms and the time series of co‐authorship as the footprints of their diffusion trajectories, we propose a novel method to analyze the intertwining relationships between broadcasting and virality in the innovation diffusion process. Our findings show that broadcasting and virality have similar diffusion power, but play different roles across diffusion stages. Broadcasting is more powerful in the early stages but may be gradually caught up or even surpassed by virality in the later period. Meanwhile, diffusion speed in virality is significantly faster than broadcasting and members from virality channels tend to adopt the same innovation repetitively.

Grouting rock fractures under condition of flowing water

Grouting is generally applied as an effective way to seal rock fractures, reduce permeability, decrease deformation, increase strength of rocks, and to stop the water flow through the jointed rock mass. But grouting rock fractures under condition of flowing water depends greatly on experiences of professional engineers, without sufficient theoretical guidance to refer to, as no commonly accepted and reasonable theoretical models are available. To describe the grouting process of fractures in flowing water, and put forward reasonable grouting guidance suggestions. The present work established a theoretical model for grouting into a fracture with flowing water. Considering boundary conditions, a streamline equation of grouting diffusion trajectory with flowing water was derived, and analyzed the influence of boundary effect on grouting diffusion law. The simulation tests of grouting rock fracture with flowing water were carried out on the self-developed fracture grouting experimental platform, and the results were compared with the theoretical prediction results, which verified the rationality of the theoretical model. The results show that there are three types of diffusion of quick-setting slurry under condition of flowing water. The existence of boundaries can increase the penetration along the direction of the flowing water both downstream and upstream, but it weakens the penetrability in the vertical flow direction. Rock fractures with a high water velocity require a high grouting flow rate, however, it is not the higher the better for determining the relevant grouting flow rate, a decrescent ratio between these two parameters should be ensured as a precondition.

Monte Carlo tracking drift-diffusion trajectories algorithm for solving narrow escape problems

Abstract This study deals with a narrow escape problem, a well-know difficult problem of evaluating the probability for a diffusing particle to reach a small part of a boundary far away from the starting position of the particle. A direct simulation of the diffusion trajectories would take an enormous computer simulation time. Instead, we use a different approach which drastically improves the efficiency of the diffusion trajectory tracking algorithm by introducing an artificial drift velocity directed to the target position. The method can be efficiently applied to solve narrow escape problems for domains of long extension in one direction which is the case in many practical problems in biology and chemistry. The algorithm is meshless both in space and time, and is well applied to solve high-dimensional problems in complicated domains. We present in this paper a detailed numerical analysis of the method for the case of a rectangular parallelepiped. Both stationary and transient diffusion problems are handled.

A multi-phase mesoscopic simulation model for the diffusion of chloride in concrete under freeze–thaw cycles

Reinforced concrete (RC) structures in cold regions are subjected to double attacks of chloride erosion and freeze–thaw cycles (FTCs), accelerating the deterioration of concrete performance. Here, a multi-phase mesoscopic numerical model is proposed to systematic study the diffusion mechanism of chloride under the FTCs. Unlike most of existing models, the interface transition zone (ITZ) with random thickness is taken into account in the proposed concrete meso-structure. Moreover, the relationship between FTCs damage and chloride diffusion coefficient of concrete is deduced from the classical Aas-Jakobsen S-N equation. The reliability of the proposed model is further verified by compared with the third-party experiments data. It is evident from the proposed model that FTCs can promote the chloride diffusion. More importantly, this promoting effect is obvious when the number of FTCs is close to the limit number of FTCs. Specially, the mechanism of ITZ promoting the chloride diffusion is revealed by simulating the chloride diffusion trajectories in concrete meso-structure. Interestingly, despite the existence of FTCs in cold regions, chloride is diffused more rapidly in the tropical regions. Our findings reveal previously ignored fundamental aspects of the chloride diffusion mechanism under FTCs, and provide insights for the durability prediction of RC structures.

Evaluation of Amorphous Oxide Coatings for High-Voltage Li-Ion Battery Applications Using a First-Principles Framework.

Cathode surface coatings are widely used industrially as a means to suppress degradation and improve electrochemical performance of lithium-ion batteries. However, developing an optimal coating is challenging, as different coating materials may enhance one aspect of performance while hindering another. To elucidate the fundamental thermodynamic and transport properties of amorphous cathode coating materials, here, we present a framework for calculating and analyzing the Li+ and O2- transport and the stability against delithiation in such materials. Our framework includes systematic workflows of ab-initio molecular dynamics calculations to obtain amorphous structures and diffusion trajectories coupled with an analysis of critical changes of the active-ion local environment during diffusion. Based on these data, we provide an estimate of room-temperature diffusivities, including statistical error bars, and the evaluation of the coating suitability in terms of its ability to facilitate Li+ transport while blocking O2- transport. Finally, we add the thermodynamic stability analysis of the coating chemistry within the operating voltage of common Li-ion cathodes. We apply this framework to two commonly used amorphous coating materials, Al2O3 and ZnO. We find that (1) in general, a higher Li+ content increases both Li+ and O2- diffusivities in both Al2O3 and ZnO. Also, Li+ and O2- diffuse much faster in ZnO than in Al2O3. (2) However, neither Al2O3 nor ZnO is expected to retain a significant concentration of Li+ at high charge. (3) ZnO performs much more poorly in terms of O2- blocking, and hence, Al2O3 is preferred for high-voltage cathode applications. These results will help to quantitatively evaluate amorphous materials, such as metal oxides and fluorides, for different performance metrics and facilitate the development of optimal cathode coatings.

Exchange-Traded Funds on European Markets: Has Critical Mass been Reached? Implications for Financial Systems.

Exchange-traded funds (ETFs) are one of the most rapidly expanding categories of financial products in Europe. One of the key yet still unanswered questions is whether European ETF markets have reached the size at which they could affect the financial systems. In our study, we examine 13 European countries during the period 2004–2017 in order to trace whether the share of ETFs in the total assets of investment funds has reached the ‘critical’ level that makes possible their further growth and can be associated with an influence on the financial system. We use a novel methodological approach that identifies the ‘critical mass’ along diffusion trajectories. Our results show that, in 10 countries, the share of ETFs in assets of investment funds increased. Still, in most countries, the share of ETFs did not exceed 1%. Estimates of the diffusion models indicate that the process of growing shares of ETFs was most dynamic and relatively most stable in Switzerland and United Kingdom. Results of the critical mass analysis imply that its achievement may be forecasted exclusively in these two cases. However, even in such cases there is no substantial evidence for a possible significant influence of ETFs on the local financial systems.

The spatial spread of dockless bike-sharing programs among Chinese cities

In a short period of three years from 2016 to 2018, the latest generation of dockless bike-sharing programs that originated in Beijing have gone through a roller coaster ride of boom to bust. While their spatial presence has been highly visible globally, the rationale, process and outcomes of the spatial spread as well as the strategies and agents behind the spatial diffusion have so far been unknown. This paper explores the geography of diffusion of dockless bike-sharing programs by analysing data collected from multiple sources. The findings reveal that the geography of diffusion was itself a business strategy for entrepreneurs to manage competition. Dockless bike-sharing fleets were placed selectively in cities worldwide by aggressive program operators supported by profit-hungry venture capital. The push by these supply-side agents in the diffusion process makes it unique from the diffusion studies which focused on users. An uneven landscape is discernible in the diffusion outcomes characterised by the clusters of similar cities where dockless bike-sharing programs are either present or absent, and the outlier clusters which are surrounded by dissimilar neighbours. The process through which an uneven landscape was developed presents two contrasting diffusion trajectories – from large to small cities vs from small to large cities.

What Can We Learn from Carbon Nanotube Diffusion Trajectories Recorded in the Live Brain?

Luminescent single wall carbon nanotubes are now well established, as unique nanoreporters to probe the brain extracellular space[1-3]. On the imaging side, this comes from their rich near-infrared optical properties, which also eventually be improved by sp3-chemical functionalization. In addition, their uncommon 1D morphology is an important asset for tissue penetration, yet understanding their diffusion behavior in the complex brain extracellular network is challenging and necessitates dedicated analysis tools. To this aim, we propose novel approaches (i) based on the local analysis of trajectory contours to locally measure the nanoscale dimensions of the brain network [4] and (ii) based on the transient evaluation of carbon nanotube mean square displacement to delineate the ECS molecular diffusion landscape [5]. The application of these analytical tools to extract relevant biological parameters in physiological and pathological brain models will be presented [6].

Activation and selectivity of OTUB-1 and OTUB-2 deubiquitinylases

The ovarian tumor domain (OTU) deubiquitinylating cysteine proteases OTUB1 and OTUB2 (OTU ubiquitin aldehyde binding 1 and 2) are representative members of the OTU subfamily of deubiquitinylases. Deubiquitinylation critically regulates a multitude of important cellular processes, such as apoptosis, cell signaling, and growth. Moreover, elevated OTUB expression has been observed in various cancers, including glioma, endometrial cancer, ovarian cancer, and breast cancer. Here, using molecular dynamics simulation approaches, we found that both OTUB1 and OTUB2 display a catalytic triad characteristic of proteases but differ in their configuration and protonation states. The OTUB1 protein had a prearranged catalytic site, with strong electrostatic interactions between the active-site residues His265 and Asp267 In OTUB2, however, the arrangement of the catalytic triad was different. In the absence of ubiquitin, the neutral states of the catalytic-site residues in OTUB2 were more stable, resulting in larger distances between these residues. Only upon ubiquitin binding did the catalytic triad in OTUB2 rearrange and bring the active site into a catalytically feasible state. An analysis of water access channels revealed only a few diffusion trajectories for the catalytically active form of OTUB1, whereas in OTUB2 the catalytic site was solvent-accessible, and a larger number of water molecules reached and left the binding pocket. Interestingly, in OTUB2, the catalytic residues His224 and Asn226 formed a stable hydrogen bond. We propose that the observed differences in activation kinetics, protonation states, water channels, and active-site accessibility between OTUB1 and OTUB2 may be relevant for the selective design of OTU inhibitors.

Visualizing Arc mRNA transfer using single molecule fluorescence assays

The transfer of genetic material between cells has been implicated in both maintaining neuronal function as well as the proliferation of many diseases and disorders, especially neurodegenerative disorders. Regulation of mRNA transfer through transport and localization is conducted by RNA binding proteins (RBPs), making RBPs responsible for control of gene expression. The activity‐regulated cytoskeleton‐associated protein, Arc, is an important component of maintaining neuronal synaptic plasticity which ensures the proper flow of cognitive information. In Alzheimer’s disease, an increase of Arc protein expression and localization in synaptic activity areas has been observed in compensating for memory and cognition loss. Although Arc is thought to be released from the synaptic cleft through Arc‐formed capsids to transfer Arc mRNA into new target cells, the mechanism of action is unknown. This project uses single molecule fluorescence methods to interrogate the dynamics of Arc allowing for visualization of the potential movement of Arc capsids/Arc mRNA and the transfer of this genetic information in human cells. Preliminary studies of the Arc using single molecule fluorescence in situ hybridization (smFISH) and live cell imaging techniques has shown a static trajectory of Arc diffusion. Further studies of the transport and transfer of mRNA from Arc capsids will allow for an understanding how this machinery works that can be the basis for the development of new drug delivery methods for diseases with RNA targets.Support or Funding InformationNIH grant number: 1T32GM1320461